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Japan’s Lost Decade of Growth
A more recent example is Japan’s lost decade of growth, which was the
1992–2001 decade. Hayashi and Prescott (2002), treating TFP as exogenous,
find that the neoclassical growth model predicts well the path of the principal
aggregates. In particular it quantitatively predicts the large capital deepening
and the associated fall in the return on capital. It quantitatively predicts the
behavior of labor supply as well, which is further evidence for the high labor
elasticity of labor supply.
A Business Cycle Puzzle
An economic boom in the United States began with an expansion relative to
trend in early 1996 and continued to the fourth quarter of 1999. Then, a
contraction set in and continued until the third quarter to 2001. At the peak,
detrended GDP per working-age person was 4 percent above trend and labor
supply 5 percent above average. None of the obvious candidates for the high
labor supply were operating. There was no war with temporarily high public
consumption that was debt financed; tax rates were not low; TFP measured in
the standard way was not high; and there was no monetary surprise that
would give rise to high labor supply. This is why I say this boom is a puzzle for
the neoclassical growth model.
Why did people supply so much labor in this boom period? The work of
McGrattan and Prescott (2005a), which determines the quantitative predic-
tions of theory for the value of the stock markets, suggests an answer. The
problem is one of measurement. During this period (see McGrattan and
Prescott, 2005b), there is evidence that unmeasured investment was high, as
was unmeasured compensation. Therefore, output and productivity were higher
than the standard statistics indicate. The measurement problem is to come up
with estimates of this expensed investment. With these improved measure-
ments of economic activity, theory can be used to determine whether or not
the puzzle has been solved.
This example illustrates the unified nature of aggregate economics today.
The real business cycle model was extended and used to understand the
behavior of the stock market, and that extended model in turn is now being
used to resolve a business cycle puzzle.
8. RAGNAR FRISCH’S VISION REALIZED
I conclude this address with an ode to Frisch, who was awarded the first
Nobel Prize in Economics in 1969. Frisch’s Nobel address is entitled “From
Utopian Theory to Practical Applications: The Case of Econometrics” (1970).
He is the father of quantitative neoclassical economics, which is what he is re-
ferring to by the word econometrics in the title.
14
14
Frisch (1970, p. 12) reports that the English mathematician and economist Jevons (1835–1882)
dreamed that we would be able to quantify neoclassical economics.
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392
Prior to Frisch’s creating the Econometric Society in 1930 and launching
Econometrica in 1933, neoclassical economists did little to verify their theoreti-
cal results by statistical observations. Frisch writes in his Nobel address that
the reason was in part the poor quality of statistics then available and in part
that neoclassical theory was not developed with systematic verification in view.
The American Institutionalists and German Historical schools pointed this
out and advocated letting the facts speak for themselves. The impact of these
schools on economic thought was minimal. To quote Frisch, “Facts that speak
for themselves, talk in a very naive language” (1970, p. 16). Now theory derives its
concepts from measurement, and in turn theory dictates new measurement.
The latter is what McGrattan and I are currently doing to resolve the puzzle of
why U.S. employment was so high at the end of the 1990s.
In the 1960s Frisch was frustrated by the lack of progress in his quest to
making neoclassical economics quantitative and referred to much of what
was being done then as “playometrics.” It is a little unfair to criticize those
studying business cycles at that time for not using the full discipline of neo-
classical economics. All the needed tools were not yet part of the economist’s
tool kit. Some of these tools that are crucial to the study of business cycles are
Lindal’s extension of general equilibrium theory to dynamic environments;
Savage’s statistical decision theory as uncertainty is central to business cycles;
Arrow and Debreu’s extension of general equilibrium theory to environments
with uncertainty; Blackwell’s development of recursive methods which are
needed in computation and in representation of a dynamic stochastic equili-
brium; Lucas and Prescott’s development of recursive competitive equilibrium
theory;
15
and, of course, the computer.
Particularly noteworthy is Lucas’s role in the macroeconomic revolution.
In the very late 1960s and early 1970s he revolutionized macroeconomics by
taking the position that neoclassical economics should be used to study busi-
ness cycles. Others had dreamed of doing it, but Lucas actually figured out
ways to do it. In his 1972 paper “Expectations and the Neutrality of Money,”
he creates and analyzes a dynamic stochastic neoclassical model that displays
the Phillips curve, which is a key equation in the system-of-equations macro
models. I can think of no paper in economics as important as this one. The
key prediction based upon this theoretical analysis – namely, that there is no
exploitable trade-off between inflation and employment – was confirmed in
the 1970s when attempts were made to exploit the then perceived trade-off.
But Lucas’s work is not quantitative dynamic general equilibrium, and only
10 years later did Finn and I figure out how to quantitatively derive the im-
plications of theory and measurement for business cycle fluctuations using
the full discipline of dynamic stochastic general equilibrium theory and
15
This was further developed in Prescott and Mehra (1980). The published version of “Investment
under Uncertainty” did not include the section formally defining the recursive equilibrium with
policy and value functions depending on both an individual firm’s capacity and the industry
capacity and was an industry equilibrium analysis.
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national accounts statistics. That we have learned that business cycles of the
quantitative nature observed are what theory predicts is testimony to the
grand research program of Ragnar Frisch and to the vision and creative
genius of Robert Lucas.
On nearly every dimension I am in agreement with what Frisch advocated
in his Nobel Prize address, but on one dimension I am not. Like Frisch, I am
a fervent believer in the democratic process. The dimension on which I disagree
is how economists and policy makers should interact. His view is that the
democratic political process should determine the objective, and economists
should then determine the best policy given this objective. My view is that
economists should educate the people so that they can evaluate macroeco-
nomic policy rules and that the people, through their elective representativ-
es, should pick the policy rule. I emphasize that Finn and my “Rules Rather
than Discretion” paper finds that public debate should be over rules and that
rules should be changed only infrequently, with a lag to mitigate the time
consistency problem.
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